GPUarkitehtuurille

GPUarkitehtuurille refers to the architectural design of Graphics Processing Units (GPUs). GPUs are specialized electronic circuits designed to rapidly manipulate and alter memory to accelerate the creation of images intended for output to a display device. Unlike Central Processing Units (CPUs) which are designed for general-purpose tasks, GPUs are optimized for parallel processing, meaning they can perform many calculations simultaneously.

This parallel architecture is achieved through a large number of relatively simple processing cores, often referred to as shader units or stream processors. These cores are grouped into larger blocks, such as Streaming Multiprocessors (SMs) in NVIDIA terminology or Compute Units (CUs) in AMD terminology. Each SM/CU contains its own set of cores, along with local memory and control logic, allowing for efficient execution of identical instructions across multiple data points.

The memory hierarchy in a GPU is also a critical aspect of its architecture. GPUs typically have dedicated high-bandwidth video memory (VRAM) that is directly accessible by the processing cores. Additionally, there are often smaller, faster caches at various levels within the GPU to reduce latency and improve performance. The way data is organized and accessed within this memory system significantly impacts the overall efficiency of the GPU.

Modern GPU architectures also incorporate specialized units for tasks beyond basic graphics rendering, such as ray tracing cores for realistic lighting effects and tensor cores for accelerating artificial intelligence and machine learning workloads. The continuous evolution of GPU architectures is driven by the increasing demand for higher visual fidelity in gaming, more powerful computational capabilities in scientific research, and the rapid growth of AI applications.